Search Results - (( based optimization learning algorithm ) OR ( program optimization techniques algorithm ))

Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman by Isman, Muhammad Iskandar

“…ACO algorithm is the best solution because it included the optimization technique to optimized the result based on the data criteria needs. …”
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Dam haji game using A* search algorithm / Siti Farah Najwa Mukhlis by Mukhlis, Siti Farah Najwa

“…The results of this project is a Dam Haji game using A* algorithm which it is able to make legal movements based on the game’s rules and a matchup with a computer-based player that have gone through a process of computer learning to make movement based on the A* shortest path technique. …”
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Designing a new model for worm response using security metrics by Madihah Mohd Saudi, Taib B.M.

A Stepper Motor Design Optimization Using by Wong, Chin Wei

“…There is a need to fill this void in the area of small-motor design, and develop a program using Genetic Algorithms (GAs) as an approach to achieve optimization. …”
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection by Shing, Chiang Tan, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Lim, Pey, Yun Goh, Chee, Peng Lim

“…The stacked ensemble method uses several heterogeneous deep neural networks as the base learners. During the training and optimization process, these base learners adopt a hybrid BP and Particle Swarm Optimization algorithm to combine both local and global optimization capabilities for identifying optimal features and improving the classification performance. …”
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications. by S. Ahmed, Bestoun, Enoiu, Eduard, Afzal, Wasif, Kamal Z., Zamli

“…Hyper-heuristic is a new methodology for the adaptive hybridization of meta-heuristic algorithms to derive a general algorithm for solving optimization problems. …”
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Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Designing a New Model for Worm Response Using Security Metrics by Madihah Mohd Saudi, Taib, BM

“…Based on the experiment conducted, it produced an overall accuracy rate of 99.38 % using Sequential Minimal Optimization (SMO) algorithm. …”

Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Learning analytic framework for students’ academic performance and critical learning pathways by Lyn, Jessica Tan Yen, Goh, Yong Kheng, Lai, An Chow, Ngeow, Yoke Meng

“…The resulting reduced dataset is then subjected to various clustering algorithms, including partition-based clustering (K-means), hierarchical clustering, and density-based clustering (DBSCAN). …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…However, the most popular backpropagation algorithm which is based on Widrow-Hoff delta learning rule is not completely robust in the presence of outliers and this may cause false prediction of future values. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

“…These re suggest that machine learning driven approaches can effectively support academic administrations in making informed staffing decisions, balancing full time and part time lecturer assignments, and optimizing cost structures without compromising teaching quality. …”
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Ensemble deep learning approach for apple fruitlet detection from digital images by Yusof, Mohamad Yusnisyahmi, Ishak, Iskandar, Sidi, Fatimah

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Facilitating English Language teaching through AI- based drama in Palestine by Bsharat, Tahani, Sheikh Ahmad, Ismail

“…The findings revealed a prevailing optimism among the participating educators, indicating their confidence in the potential of AI to enhance the EFL teaching and learning experience. …”
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Hybrid of rough set theory and Artificial Immune Recognition System as a solution to decrease false alarm rate in intrusion detection system by Sabri F.N.M., Norwawi N.M., Seman K.

Linear array beampattern gain optimization techniques by Nagi F.

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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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Congestion management based optimization technique using bee colony by Rahim M.A., Musirin I., Abidin I.Z., Othman M.M., Joshi D.

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